From mdyer@top.cis.syr.edu Thu May 19 12:26:30 1994
Date: Thu, 19 May 94 11:52:35 EDT
From: Michelle Dyer <mdyer@top.cis.syr.edu>
To: cis_all@top.cis.syr.edu, cis_grads@top.cis.syr.edu,
    cis_undergrads@top.cis.syr.edu, cis_affiliated_faculty@top.cis.syr.edu,
    seminars@nova.npac.syr.EDU
Subject: CIS SEMINAR - Friday, June 3 - Francine Chen










Francine Chen
Xerox PARC




Detection and Location of Partially-Specified Keywords 
and Phrases in Scanned Images using Hidden Markov Models




2:00 PM, Friday, June 3, 1994 - Rm. 1-218 CST
Refreshments -  3:00 PM  Room 4-133 CST




We are developing a hidden Markov model (HMM) based system for
detecting and locating, or spotting, user-specified keywords and
phrases in scanned images.  The system is font-independent and does
not require pre-segmentation of text and graphics.  In our system,
the bounding boxes of potential lines of text are extracted from
the image using morphology, and keywords are identified within each
line.  Feature vectors are computed over vertical columns of pixels
in each bounding box and describe the external shape and internal
structure of the characters.  For each user-specified keyword, an
HMM is created by concatenating appropriate context-dependent
character HMMs.  Graphics and words in the image which are not
keywords are modeled by a non-keyword HMM created from
context-dependent sub-character models.  Keywords are spotted using
Viterbi decoding on an HMM network created from the keyword and
non-keyword HMMs.  This model allows detection of keywords embedded
in a line without pre-segmentation of the line into words or
characters.  Thus keywords may be specified by a baseform, and
variants of the keyword can be detected.

This is joint work with Lynn Wilcox and Dan Bloomberg.


